Mangrove Forest Health Assessment on Small Island in Maluku

The study aims to assess the health condition of mangrove forests on Ambon Island using the approach of tree damage value, forest damage and tree productivity value. The study was conducted in the Mangrove Forest area at 128014’40.680” N and 3038’6.358 S on Ambon Island. The study at the tree level consisted of 3 clusters of 4 subplots measuring 1 ha. Analysis of mangrove forest health using the forest health monitoring method in three clusters with parameters of tree health, forest health and forest productivity. The study results found the types of Sonneratia alba, Rhizophora stylosa, Avicennia marina, Aegiceras corniculatum, and Bruguiera gymnorrhiza. The tree damage value (CLI) ranged from 10.680 until 11.901, with the highest damage in cluster 2 being 11,901 and the lowest in cluster 1 being 10,680. The higher the tree damage value (CLI), the higher the damage or unhealthy condition. Mangrove forest damage in Passo Village is due to tree termite attacks (Prorhinotermes flavus), which attack the lower tree trunks, with a high category attack intensity of 65.5%. The health condition of the mangrove forest in cluster 1 is better than other clusters, with a low damage value (CLI) of 10,680. In cluster 1, no inorganic waste was found that could cause damage to young plants. The highest LBDS value in Sonneratia alba is 26,689, 27,9070 individuals. The study's findings are crucial for the conservation and management of mangrove forests, engaging the audience in the importance of these efforts.

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Publication Details

Journal
International Journal on Advanced Science Engineering and Information Technology
Published
2024-12-26
DOI
https://doi.org/10.18517/ijaseit.14.6.20361
Citations
1
Primary Topic
Forest Ecology and Conservation
Type
article
Field-Weighted Citation Impact
2.07
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article

Mangrove Forest Health Assessment on Small Island in Maluku

Fransina Latumahina, Rahman Rahman, Susi Susilawati
1 citations
International Journal on Advanced Science Engineering and Information Technology
Forest Ecology and Conservation
2.07
article

Mangrove Forest Health Assessment on Small Island in Maluku

Fransina Latumahina, Rahman Rahman, Susi Susilawati
article en
1 citations

Abstract

The study aims to assess the health condition of mangrove forests on Ambon Island using the approach of tree damage value, forest damage and tree productivity value. The study was conducted in the Mangrove Forest area at 128014’40.680” N and 3038’6.358 S on Ambon Island. The study at the tree level consisted of 3 clusters of 4 subplots measuring 1 ha. Analysis of mangrove forest health using the forest health monitoring method in three clusters with parameters of tree health, forest health and forest productivity. The study results found the types of Sonneratia alba, Rhizophora stylosa, Avicennia marina, Aegiceras corniculatum, and Bruguiera gymnorrhiza. The tree damage value (CLI) ranged from 10.680 until 11.901, with the highest damage in cluster 2 being 11,901 and the lowest in cluster 1 being 10,680. The higher the tree damage value (CLI), the higher the damage or unhealthy condition. Mangrove forest damage in Passo Village is due to tree termite attacks (Prorhinotermes flavus), which attack the lower tree trunks, with a high category attack intensity of 65.5%. The health condition of the mangrove forest in cluster 1 is better than other clusters, with a low damage value (CLI) of 10,680. In cluster 1, no inorganic waste was found that could cause damage to young plants. The highest LBDS value in Sonneratia alba is 26,689, 27,9070 individuals. The study's findings are crucial for the conservation and management of mangrove forests, engaging the audience in the importance of these efforts.

International Journal on Advanced Science Engineering and Information TechnologyVol. 14(6)
University of Pattimura (ID), Lambung Mangkurat University (ID)
Life in Land
Openalex Percentile: Top 9%
Forest Ecology and Conservation
2.07
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Mangrove Forest Health Assessment on Small Island in Maluku — Fransina Latumahina, Rahman Rahman, et al. · International Journal on Advanced Science Engineering and Information Technology (2024) | TGRS Research Map | TGRS